1. Field of the Invention
The present invention relates to semiconductor processing, and more particularly, endpoint detection during semiconductor plasma processing using optical emission spectroscopy.
2. Description of Related Art
Plasma processing is often employed in manufacturing integrated circuits. Plasma processing uses the action of an electrically conductive gas, composed of ionized gas or molecules, to remove unwanted portions of conductive or insulative patterns. It includes plasma cleaning as a removal of photoresist or plasma based etching of thin films or selected portions of layers of materials on semiconductor wafer substrates. Under ideal semiconductor processing conditions, such plasma etching of a film can be accomplished by using the process for a predefined time. However, variations in material thickness and quality, as well as variation in process operating conditions, are typically difficult to control, and make a timing-based system generally infeasible. A simpler approach has been to process for the longest possible time, thereby ensuring that all wafers are processed to completion. This over-processing has its drawbacks. First, wafers with relatively short clearing times will be subject to the processing plasma for a long time and can incur damage or degradation of the layer beneath the one being etched, since this layer generally should not be etched at all. Second, unnecessarily long processing reduces the throughput of the processing tool and uses too much precursors, thereby increasing the cost of processing.
The prior art has also employed chemical analysis to detect the end-of-process (EOP), or endpoint when the film layer has been completely removed. As the plasma process proceeds, there is a change in the chemical constituents in the plasma, corresponding to the removal of the desired film layer. Since the plasma glows, i.e., gives off light, this change in the constituents may be detected by any device that analyzes specific parts of the spectrum. The cheapest method is using a filter that would filter out a specific desired wavelength, and detect that wavelength.
Another alternative is to use a spectrometer which collects all wavelengths at one time and then detects a specific wavelength or combination of wavelengths and performs mathematical processing of those to determine what has occurred. For example, the component being removed is normally dropping in concentration, while the underlying component may be increasing in concentration, if it begins to be removed. One may look at these components separately, or may take a ratio of these two components in the plasma spectra to enhance the signal. Since the spectrograph normally collects all wavelengths, the process is still difficult since one must determine the wavelength(s) on which to concentrate. Some of the software employed for these techniques are exceptionally complicated, and require still greater knowledge of other concepts, and the tracking and manipulation of many parameters. A typical setup for a current state-of-the-art EOP system involves the following steps:    1) Define detector parameters. Typically a detector such as a mutli-channel charged coupled device (CCD) spectrograph, will have at minimum three parameters: i) Exposure time—the time required to expose the CCD to light, also know as integration time, ii) Sample average—the number of exposures averaged together to yield a spectral data set, iii) Sample interval—the time between the transfer of the spectral data set to the processing device. Other parameters may include: gain on the amplifier between the CCD array and the analog-to-digital converter, temperature control of the CCD, a base line offset, and the like.    2) Set spectrum source. Typical endpoint software packages are very general and require the user to input the actual type of detector, and the range of wavelengths to be processed. Some have the potential for multiple sources, including previously collected data.    3) Select spectrum regions. Regions of the spectrum are selected depending on the nature of subsequent analysis. Parts of the spectrum may be selected, such as single peaks, or bands, or segments of the spectrum. These are usually expressed as the average or the sum of the indicated region. These can be designated as R1, R2, R3, . . . RN.    4) Define equations. Typical current state-of-the-art (current art) endpoint software requires the construction of an equation from the R1, R2, R3, . . . RN. The equation can be a mathematical combination of the R1, R2, R3, RN, which can include addition, subtraction, multiplication, division and higher math functions.    5) Setup full spectrum parameters. If additional treatment of the spectral data is required, which is not covered by the equations, the current art software will have a “special” window for this set up. Usually this will require several parameters. To use these parameters will require extensive knowledge of higher mathematical theory for proper use.    6) Setup endpoint signal analysis parameters. At this point the setup procedure has provided for the generation of a single datum at a give time T. The entire set of these time dependent data can be called the endpoint curve (EPC). Parameters are required to condition the EPC signal. At times the EPC can be noisy and needs to be smoothed, or filtered. A filter parameter needs to be setup. Some EPCs do not have distinct endpoint characteristics. If that is the case then further processing is required. Usually the derivative, or slope, needs to be computed. Most slopes require further smoothing. Often times the signal needs to be normalized at this point normalization parameters need to be specified.    7) Setup endpoint detection parameters. Once the EPC has been conditioned, it then has to be analyzed to determine if endpoint has occurred. Several methods exist for this analysis. The most common is the threshold method, where the EPC as it evolves in time will cross a some predetermined value, either increasing such that it is greater than that value, or decreasing such that it is less than that value. Generally this requires several parameters.    8) Define minimum and maximum process times. The minimum time is the time before which no clearing of any film can occur and the endpoint algorithm will ignore all signals prior to that time. The maximum process time is the time after which no further processing should occur. Generally if the process duration is near this time some sort of error has occurred.
Most current art software applications will have a separate window, display or tab for each of the eight above-mentioned steps. The use of this software application typically entails the reading of a lengthy set of instructions and often, special training such as a class.
In addition to the above complexities, the endpoint algorithm on some existing systems is inadequate for advanced applications such as barrier etch, poly etchback and critical cleans, since some of these processes have small exposed areas of film subject to etch. This results in very small signal changes. It is therefore important to reduce noise, provide for methods ensuring a robust algorithm, and appropriately scale the display such that the process engineer can see the change.